Digital images, especially those that have been generated by a capture device such as, but not limited to, a scanner, multifunction machine, and a camera, contain features that may benefit from enhancement. For example, natural scene images are often enhanced to improve sharpness or to smooth the image using one or more filtering approaches. Similarly, when capturing text using a scanner or similar device, scanned text may result that is either too narrow or too wide as a result of various optical distortions and sampling related causes. Emboldening and thinning techniques may be applied in such instances to correct or adjust the scanned text.
Various image processing methodologies are available for the enhancement of digital images that either embolden or thin features in a digital image. Clipping or shifting a gamma mid-point of a tone curve of a digital image may be used as a crude means of emboldening or thinning features. A technique referred to as an ‘unsharp mask’ is another example of means for emboldening or thinning digital image features. The local area contrast enhancement (LACE) technique is a competitor to the unsharp mask. Techniques from mathematical morphology techniques may provide either emboldening or thinning. For example, dilation may be employed to make a foreground element thicker resulting in emboldening. Yet other techniques that provide thinning, but cannot be employed for emboldening or thickening, include erosion and the so-called ‘hit-or-miss transform’.